典型文献
Gaussian-Student's t mixture distribution PHD robust filtering algorithm based on variational Bayesian inference
文献摘要：
Aiming at the problem of filtering precision degradation caused by the random outliers of process noise and measurement noise in multi-target tracking(MTT)system,a new Gaussian-Student's t mixture distribution probability hypothesis density(PHD)robust filtering algorithm based on variational Bayesian inference(GST-vbPHD)is proposed.Firstly,since it can accurately describe the heavy-tailed characteristics of noise with outliers,Gaussian-Student's t mixture distri-bution is employed to model process noise and measurement noise respectively.Then Bernoulli ran-dom variable is introduced to correct the likelihood distribution of the mixture probability,leading hierarchical Gaussian distribution constructed by the Gaussian-Student's t mixture distribution suit-able to model non-stationary noise.Finally,the approximate solutions including target weights,measurement noise covariance and state estimation error covariance are obtained according to varia-tional Bayesian inference approach.The simulation results show that,in the heavy-tailed noise envi-ronment,the proposed algorithm leads to strong improvements over the traditional PHD filter and the Student's t distribution PHD filter.
文献关键词：
中图分类号：
作者姓名：
HU Zhentao;YANG Linlin;HU Yumei;YANG Shibo
作者机构：
School of Artificial Intelligence,Henan University,Zhengzhou 450046,P.R.China;School of Automation,Northwestern Polytechnical University,Xi'an 710029,P.R.China
文献出处：
引用格式：
[1]HU Zhentao;YANG Linlin;HU Yumei;YANG Shibo-.Gaussian-Student's t mixture distribution PHD robust filtering algorithm based on variational Bayesian inference)[J].高技术通讯（英文版）,2022(02):181-189
A类：
vbPHD
B类：
Gaussian,Student,mixture,distribution,robust,filtering,algorithm,variational,Bayesian,inference,Aiming,problem,precision,degradation,caused,by,random,outliers,process,noise,measurement,multi,target,tracking,MTT,system,new,probability,hypothesis,density,GST,proposed,Firstly,since,can,accurately,describe,heavy,tailed,characteristics,employed,model,respectively,Then,Bernoulli,variable,introduced,correct,likelihood,leading,hierarchical,constructed,suit,stationary,Finally,approximate,solutions,including,weights,covariance,state,estimation,error,are,obtained,according,approach,simulation,results,show,that,envi,ronment,leads,strong,improvements,over,traditional
AB值：
0.474307
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